Towards Optimal Production of Graphene by Electrolysis in Molten Salts Using Machine Learning

Authors

  • Viktor Andonovikj Faculty of Electrical Engineering and Information Technologies, North Macedonia
  • Mimoza Kovaci Azemi Faculty of Geodetic Sciences and Technology, “Xasan Pristina” University, Mitrovica, Republic of Kosovo
  • Beti Andonovic Faculty of Technology and Metallurgy, St. Cyril and Methodius University, Skopje, North Macedonia https://orcid.org/0000-0002-5386-457X
  • Aleksandar Dimitrov Faculty of Technology and Metallurgy, St. Cyril and Methodius University, Skopje, North Macedonia https://orcid.org/0000-0002-8845-0641

DOI:

https://doi.org/10.54820/entrenova-2023-0007

Keywords:

graphene, electrolysis, graphite, molten salts, machine learning

Abstract

Graphene is very exciting and one of the best materials in the last decade. The interest in producing non-expensive and high-quality graphene is of great interest to many Departments of materials and researchers worldwide. The main goal of this research considers the design, development, and optimisation of new technology for producing graphene by electrolysis in molten salts using constant cell voltage, reversing cell voltage, and constant overpotential and reversing overpotential methods. Compared to other processes, the electrolysis process is simple, ecological, and economical. Furthermore, it offers possibilities to control various parameters: type of electrolyte, applied voltage, current density, temperature and type of graphite used as a row material for synthesis of graphene. The underlying relationship between the parameters and the quality of the graphene is obtained through an explainable tree-based Machine Learning (ML) model. We trained the model by using the production process parameters as input attributes and the quality of the produced graphene as a target variable. Domain experts provide labels regarding the quality of each experimental instance in our data set. We propose using the extracted rules from the model to serve as a blueprint for optimal graphene production by electrolysis in molten salts. Choosing the correct values for the process parameters results in high-yield graphene production, up to ten times cheaper than the one produced with other existing technologies.

Author Biographies

Viktor Andonovikj, Faculty of Electrical Engineering and Information Technologies, North Macedonia

Viktor Andonovikj is a PhD student in ICT and a young researcher at Jožef Stefan Institute, Ljubljana, Slovenia. He is working on the development of decision support systems for Public Employment Services, including advanced models based on machine learning and graph theory. He has completed several Short-Term Scientific Missions financed by EU H2020 projects and is an author of scientific articles published in relevant journals. The author can be contacted at viktor.andonovikj@ijs.si

Mimoza Kovaci Azemi, Faculty of Geodetic Sciences and Technology, “Xasan Pristina” University, Mitrovica, Republic of Kosovo

Mimoza Kovaci Azemi works as a teaching assistant at the Faculty of Geodetic Sciences and Technology, “Xasan Pristina” University, Mitrovica, Republic of Kosovo, where she has acquired her Bachelor’s and Master’s Degree in metallurgy in the field of materials. She is currently a PhD student in metallurgy at the Faculty of Technology and Metallurgy, Skopje, North Macedonia. The author can be contacted at mimoza.kovaci@umib.net

Beti Andonovic, Faculty of Technology and Metallurgy, St. Cyril and Methodius University, Skopje, North Macedonia

Beti Andonovic, PhD is an Associate Professor at the Faculty of Technology and Metallurgy, Skopje, Macedonia. She obtained her PhD in mathematics at the Faculty of Mathematics and Natural Sciences, University St. Cyril and Methodius, Skopje, Macedonia, in 2009. She was Head of the Department of Chemical and Control Engineering at the Faculty of Technology and Metallurgy 2012-2016. She is the author of many scientific articles in mathematics and mathematical modelling, as well as in management, and is the author of two University books on the subjects of Mathematics and Communication skills. She has presented her scientific research at numerous international conferences and has given invited talks at Universities in Macedonia and abroad. The author can be contacted at beti@tmf.ukim.edu.mk

Aleksandar Dimitrov, Faculty of Technology and Metallurgy, St. Cyril and Methodius University, Skopje, North Macedonia

Aleksandar Dimitrov, PhD is a Full Professor at the Faculty of Technology and Metallurgy, Skopje, North Macedonia, and Head of the Department of Extractive Metallurgy. He completed postdoctoral studies at the Department of Material Science and Metallurgy, University of Cambridge, Cambridge, UK. Dimitrov is an author of more than 100 international scientific articles and has participated in many international conferences as an invited lecturer. He has had numerous research and scientific missions in many universities, including the University of Cambridge, University of Leeds, University of Oxford, UK, and others. His current research is focused on nanomaterials and nanostructures, particularly on synthesising graphene, MWCNTs, and other carbon nanomaterials and quality management. Dimitrov is a current MC member in EU projects COST Actions CA17139 and CA17140 and has been a leader of many international projects. The author can be contacted at: aco2501@gmail.com

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Published

2024-03-12

How to Cite

Andonovikj, V. ., Kovaci Azemi, M., Andonovic, B. ., & Dimitrov, A. . (2024). Towards Optimal Production of Graphene by Electrolysis in Molten Salts Using Machine Learning. ENTRENOVA - ENTerprise REsearch InNOVAtion, 9(1), 62–71. https://doi.org/10.54820/entrenova-2023-0007

Issue

Vol. 9 No. 1 (2023)

Section

Mathematical and Quantitative Methods

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Copyright (c) 2024 Viktor Andonovikj, Mimoza Kovaci Azemi, Beti Andonovic, Aleksandar Dimitrov

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